The expert team formed by the MIFA Laboratory of the Shanghai Jiao Tong University Qingtuan Research Institute and the Endocrinology Department of Zhongshan Hospital affiliated with Fudan University has recently developed a dedicated large model for diabetes named Diabetica. This model integrates the language processing capabilities of large models with specialized knowledge in diabetes, aiming to provide intelligent support for doctors, patients, and medical education. The team employed a novel framework to establish a comprehensive data processing system, created high-quality datasets and evaluation benchmarks, and fine-tuned the large language model, significantly enhancing its performance on diabetes-related tasks.

Recently, an international team of researchers from China and Singapore successfully developed the world's first multi-modal artificial intelligence system for diabetes diagnosis and treatment, DeepDR-LLM. The research findings were published in Nature Medicine on July 19, 2024.

Researchers at Klick in Canada have released an AI large model that can diagnose type 2 diabetes in just 6 to 10 seconds using voice. Validation with 267 volunteer voice samples showed an accuracy rate of 89% for females and 86% for males. The study identified 'pitch' and 'pitch standard deviation' as key diagnostic features. Various models, including logistic regression and naive Bayes, were used for training and testing. The integrated module combines multiple information sources to improve model accuracy and offers potential for early intervention.

AI can detect type 2 diabetes by merely listening to a patient's speech for 6-10 seconds. Research shows an accuracy rate of 89% in females and 86% in males. The study analyzed over 18,000 recordings using voice technology, successfully identifying differences in voice between diabetic and non-diabetic patients.